Spatio-Temporal Volume Data Aggregation for Crowdsensing in VDTN

Abstract

In this paper, we propose a spatio-temporal data aggregation protocol in Vehicular Delay Tolerant Network (VDTN). We focus on Asynchronous Vehicular Crowdsensing Service (AVCS) to collect volume sensor data (e.g., images captured by on-board cameras) from VDTN-enabled vehicles. In AVCS, it is critical to cope with the huge redundant traffic generated by a large number of vehicles. We propose a novel protocol to aggregate volume spatio-temporal sensor data in Hybrid DTN data collection architecture. By assigning spatio-temporal identifiers (STI) to the aggregation targets in AVCS and extending the message exchange protocol to treat STI in VDTN, the redundant traffic can be significantly improved. Simulation results using a real taxi trace dataset showed the effectiveness of the proposed data aggregation protocol. The coverage of the crowdsensing was improved around 20-35% with 80% traffic reduction compared with the baseline aggregation protocol.